The impact of fecal sample processing on prevalence estimates for antibiotic-resistant Escherichia coli

Omulo, Sylvia; Lofgren, Eric; Mugoh, Maina; Alando, Moshe; Obiya, Joshua; Kipyegon, Korir; Kikwai, Gilbert; Gumbi, Wilson; Kariuki, Samuel; Call, Douglas R.

doi:10.1016/j.mimet.2017.03.006

Cited by 8 publications

(8 citation statements)

References 18 publications

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“…Additionally, although risk factors for antimicrobial resistance in the Arusha and Maasai were associated with multiple antibiotics, the few risk factors in the Chagga were only associated with one antibiotic, which increases the chance for spurious associations. The microbiology methods used in this study were the most practical given logistic realities, 28 but we acknowledge that identification of E coli by colony morphology only could lead to misidentification. In an associated whole-genome-sequencing project based on a subset of bacteria from this study, 9% of isolates from human stool samples presumed to be E coli were actually Enterobacter or Klebsiella species ( appendix ).…”

Section: Discussionmentioning

confidence: 99%

Identification of risk factors associated with carriage of resistant Escherichia coli in three culturally diverse ethnic groups in Tanzania: a biological and socioeconomic analysis

Caudell

Mair

Subbiah

et al. 2018

The Lancet Planetary Health

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SummaryBackgoundImproved antimicrobial stewardship, sanitation, and hygiene are WHO-inspired priorities for restriction of the spread of antimicrobial resistance. Prioritisation among these objectives is essential, particularly in low-income and middle-income countries, but the factors contributing most to antimicrobial resistance are typically unknown and could vary substantially between and within countries. We aimed to identify the biological and socioeconomic risk factors associated with carriage of resistant Escherichia coli in three culturally diverse ethnic groups in northern Tanzania.MethodsWe developed a survey containing more than 200 items and administered it in randomly selected households in 13 Chagga, Arusha, or Maasai villages chosen on the basis of ethnic composition and distance to urban centres. Human stool samples were collected from a subset of households, as were liquid milk samples and swabs of milk containers. Samples were processed and plated onto MacConkey agar plates, then presumptive E coli isolates were identified on the basis of colony morphology. Susceptibility of isolates was then tested against a panel of nine antimicrobials (ampicillin, ceftazidime, chloramphenicol, ciprofloxacin, kanamycin, streptomycin, sulfamethoxazole, tetracycline, and trimethoprim) via a breakpoint assay. Susceptibility findings were matched with data across a wide range of household characteristics, including education, hygiene practices, wealth, livestock husbandry, and antibiotic use.FindingsBetween March 23, 2012, and July 30, 2015, we interviewed 391 households (118 Arusha, 100 Chagga, and 173 Maasai). Human stool samples were collected at 226 (58%) households across the 13 villages. 181 milk samples and 191 milk-container swabs were collected from 117 households across seven villages. 11 470 putative E coli samples were isolated from stool samples. Antimicrobial use in people and livestock was not associated with prevalence of resistance at the household level. Instead, the factors with the greatest predictive value involved exposure to bacteria, and were intimately connected with fundamental cultural differences across study groups. These factors included how different subsistence types (pastoralists vs farmers) access water sources and consumption of unboiled milk, reflecting increased exposure to resistant bacteria in milk.InterpretationWhen cultural and ecological conditions favour bacterial transmission, there is a high likelihood that people will harbour antimicrobial-resistant bacteria irrespective of antimicrobial use practices. Public health interventions to limit antimicrobial resistance need to be tailored to local practices that affect bacterial transmission.FundingUS National Science Foundation; Biotechnology and Biological Sciences Research Council, UK Medical Research Council; and the Allen School.

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Section: Discussionmentioning

confidence: 99%

Identification of risk factors associated with carriage of resistant Escherichia coli in three culturally diverse ethnic groups in Tanzania: a biological and socioeconomic analysis

Caudell

Mair

Subbiah

et al. 2018

The Lancet Planetary Health

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“…These were then transported in cooler boxes with ice packs and stored under refrigeration for a maximum of 5 days until they were shipped to a reference laboratory at the regional hospital in Quetzaltenango where isolates of presumptive E. coli were obtained. Isolates were then tested for their susceptibility to ten antibiotics by using breakpoint assays 16,17,24 . For these assays, bacteria are grown on agar plates with fixed concentrations of antibiotic and they are considered "resistant" when growth occurs, or susceptible when growth does not occur.…”

Section: Methodsmentioning

confidence: 99%

Antibiotic use and hygiene interact to influence the distribution of antimicrobial-resistant bacteria in low-income communities in Guatemala

Ramay

Caudell

Cordón-Rosales

et al. 2020

Sci Rep

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To examine the effects of poor sanitation and hygiene on the prevalence of antimicrobial-resistant bacteria, we surveyed households in two rural and two urban communities in Guatemala (N = 196 randomly selected households). One adult (≥ 18-years old) and, when available, one child (≤ 5 yearsold) provided a stool sample. Up to 48 presumptive Escherichia coli isolates were collected from each stool sample (n = 21,256 total) and were subjected to breakpoint assays for ten antibiotics. Mixedeffects logistic models were used to identify potential factors influencing the likelihood of harboring antibiotic-resistant bacteria. For nine out of ten antibiotics, the odds of detecting resistant bacteria decreased by ~ 32% (odds ratios, OR 0.53-0.8, P < 0.001) for every unit of improvement of a hygiene scale. Hygiene differences between households had a greater impact on prevalence compared to antibiotic use differences. The likelihood of detecting resistant isolates was lower for five antibiotics among households that boiled raw milk before consumption (OR 0.31-0.69), and higher for nine antibiotics in urban households (OR > 1.89-9.6). Poor hygiene conditions likely obscure effects of individual antibiotic use, presumably due to enhanced microbial transmission. Consequently, efforts to improve antibiotic stewardship should be coupled with improving hygiene conditions. Antimicrobial-resistant infections contribute to hundreds-of-thousands of deaths worldwide 1. To address this threat, public and private organizations are engaged in programs to improve surveillance for antimicrobialresistant organisms, to improve antibiotic stewardship, and to identify novel therapeutics, all of which are considered priority actions for combating antimicrobial resistance (AMR) 2-4. The strategies adopted to limit AMR will vary globally, particularly across countries with different degrees of wealth and development. The most effective intervention will likely depend on prevailing conditions. For example, high-income countries and low-income countries can differ in antimicrobial resistance patterns, antimicrobial use practices, access to healthcare services (human and animal), sanitation and regulation infrastructures 5-9. Studies conducted within high-income countries, particularly those concerning healthcare facilities 10-12 and the agricultural sector 13-15 , have associated reductions in antimicrobial use and improved stewardship with decreases in the prevalence of antimicrobial resistance. In contrast, studies examining global patterns of AMR find that antibiotic use is not positively correlated with resistance in all cases and may instead be correlated with

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“…Colony morphology, while not a reliable diagnostic for species identity, was 99.2% consistent with E. coli based on a random subset of 248 isolates. We have successfully used this method for selecting E. coli in high-throughput eld [34][35][36]. In one study, whole-genome sequencing of 1,317 presumptive E. coli con rmed that 90.7% of the isolates collected from human stool samples were E. coli [34].…”

Section: Discussionmentioning

confidence: 99%

Carriage of antimicrobial-resistant bacteria in a high-density informal settlement in Kenya is associated with environmental risk-factors

Omulo

Lofgren

Lockwood

et al. 2020

Preprint

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BackgroundThe relationship between antibiotic use and antimicrobial resistance varies with cultural, socio-economic, and environmental factors. We examined these relationships in Kibera, an informal settlement in Nairobi - Kenya, characterized by high population density, high burden of respiratory disease and diarrhea. Methods. Two-hundred households were enrolled in a 5-month longitudinal study. One adult (≥18 years) and one child (≤5 years) participated per household. Biweekly interviews (n=1,516) were conducted and 2,341 stool, 2,843 hand swabs and 1,490 water samples collected. Presumptive E. coli (n=34,042) were isolated and tested for susceptibility to nine antibiotics.ResultsEighty percent of E. coli were resistant to ≥3 antibiotic classes. Stool isolates were resistant to trimethoprim (mean: 81%), sulfamethoxazole (80%), ampicillin (68%), streptomycin (60%) and tetracycline (55%). Ninety-seven households reported using an antibiotic in at least one visit over the study period for a total of 144 episodes and 190 antibiotic doses. Enrolled children had five times the number of episodes reported by enrolled adults (96 vs. 19). Multivariable linear mixed-effects models associated children eating soil from the household yard and informal hand-washing stations with increased numbers of antimicrobial-resistant bacteria (counts increasing by 0·27-0·80 log10 and 0·22 to 0·51 log10 respectively, depending on the antibiotic tested). Rainy conditions were associated with reduced carriage of antimicrobial-resistant bacteria (1·19 to 3·26 log10 reduction depending on the antibiotic tested).ConclusionAntibiotic use provided little explanatory power for the prevalence of antimicrobial resistance. Transmission of resistant bacteria in this setting through unsanitary living conditions likely overwhelms incremental changes in antibiotic use. Under such circumstances, sanitation, hygiene, and disease transmission are the limiting factors for controlling the presence of resistant bacteria.

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The impact of fecal sample processing on prevalence estimates for antibiotic-resistant Escherichia coli

Cited by 8 publications

References 18 publications

Identification of risk factors associated with carriage of resistant Escherichia coli in three culturally diverse ethnic groups in Tanzania: a biological and socioeconomic analysis

Identification of risk factors associated with carriage of resistant Escherichia coli in three culturally diverse ethnic groups in Tanzania: a biological and socioeconomic analysis

Antibiotic use and hygiene interact to influence the distribution of antimicrobial-resistant bacteria in low-income communities in Guatemala

Carriage of antimicrobial-resistant bacteria in a high-density informal settlement in Kenya is associated with environmental risk-factors

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